Intuitive Density Functional Theory-Based Energy Decomposition Analysis for Protein–Ligand Interactions

QM/MM-Based Energy Decomposition Analysis Method for Large Systems

In this work, a QM/MM-based EDA method, called GKS-EDA(QM/MM), is proposed. As an extension of GKS-EDA, this scheme divides the total interaction energy into electrostatic, exchange-repulsion, polarization, and correlation/dispersion terms. GKS-EDA(QM/MM) can be applied to describe the interactions of large-scale systems combined with various QM/MM platforms. By using the examples of a hydrated hydronium ion complex in water solution, the barnase-barstar complex, and MMP-13-pyrimidinetrione in a metalloprotein, the capability of GKS-EDA(QM/MM) for various interactions in large systems is validated.

Understanding the Role of Intramolecular Ion-Pair Interactions in Conformational Stability Using an Ab Initio Thermodynamic Cycle

Intramolecular ion-pair interactions yield shape and functionality to many molecules. With proper orientation, these interactions overcome steric factors and are responsible for the compact structures of several peptides. In this study, we present a thermodynamic cycle based on isoelectronic and alchemical mutation to estimate the intramolecular ion-pair interaction energy. We determine these energies for 26 benchmark molecules with common ion-pair combinations and compare them with results obtained using intramolecular symmetry-adapted perturbation theory. For systems with long linkers, the ion-pair energies evaluated using both approaches deviate by less than 2.5% in the vacuum phase. The thermodynamic cycle based on density functional theory facilitates calculations of salt-bridge interactions in model tripeptides with continuum/microsolvation modeling and four large peptides: 1EJG (crambin), 1BDK (bradykinin), 1L2Y (a mini-protein with a tryptophan cage), and 1SCO (a toxin from the scorpion venom).

A general tight-binding based energy decomposition analysis scheme for intermolecular interactions in large molecules

In this work, a general tight-binding based energy decomposition analysis (EDA) scheme for intermolecular interactions is proposed. Different from the earlier version [Xu et al., J. Chem. Phys. 154, 194106 (2021)], the current tight-binding based density functional theory (DFTB)-EDA is capable of performing interaction analysis with all the self-consistent charge (SCC) type DFTB methods, including SCC-DFTB2/3 and GFN1/2-xTB, despite their different formulas and parameterization schemes. In DFTB-EDA, the total interaction energy is divided into frozen, polarization, and dispersion terms. The performance of DFTB-EDA with SCC-DFTB2/3 and GFN1/2-xTB for various interaction systems is discussed and assessed.

PCW-1001, a Novel Pyrazole Derivative, Exerts Antitumor and Radio-Sensitizing Activities in Breast Cancer

As pyrazole and its derivatives have a wide range of biological activities, including anticancer activity, the design of novel pyrazole derivatives has emerged as an important research field. This study describes a novel pyrazole derivative that exerts antitumor and radiosensitizing activities in breast cancer both in vitro and in vivo. We synthesized a novel pyrazole compound N,N-dimethyl-N’-(3-(1-(4-(trifluoromethyl)phenyl)-1H-pyrazol-4-yl)phenyl)azanesulfonamide (PCW-1001) and showed that it inhibited several oncogenic properties of breast cancer both in vitro and in vivo. PCW-1001 induced apoptosis in several breast cancer cell lines. Transcriptome analysis of PCW-1001-treated cells showed that it regulates genes involved in the DNA damage response, suggesting its potential use in radiotherapy. Indeed, PCW-1001 enhanced the radiation sensitivity of breast cancer cells by modulating the expression of DNA damage response genes. Therefore, our data describe a novel pyrazole compound, PCW-1001, with antitumor and radiosensitizer activities in breast cancer.

Energy decomposition analysis method for metallic systems

In this work, we present the first extension of an energy decomposition analysis (EDA) method to metallic systems. We extend the theory of our Hybrid Absolutely Localized Molecular Orbitals (HALMO) EDA to take into account that molecular orbitals in metallic systems are partially occupied, which is done by weighted orthogonalization (WO) of the molecular orbitals using their associated fractional occupancies as weights in the construction of the projection operators. These operators are needed for the self-consistent field for molecular interaction (SCF MI) computation of the polarization-energy contribution to the interaction. The method gives more weight to orbitals that have higher occupancies and treats each fragment as metallic. The resulting HALMO EDA for metallic systems naturally reduces to the insulator version and produces the same results when applied to an insulating system. We present the theory and implementation of our new approach, and we demonstrate it with sample calculations of relevance to industrial materials. This work provides a new EDA paradigm and tool for the study and analysis of interactions in metallic systems within large-scale DFT calculations.

Analysis of DNA interactions and GC content with energy decomposition in large-scale quantum mechanical calculations

GC content is a contributing factor to the stability of nucleic acids due to hydrogen bonding. More hydrogen bonding generally results in greater stability. Empirical evidence, however, has suggested that the GC content of a nucleic acid is a poor predictor of its stability, implying that there are sequence-dependent interactions besides what its GC content indicates. To examine how much such sequence-dependent interactions affect the interaction energies of double-stranded DNA (dsDNA) molecules, dsDNA molecules of different sequences are generated and examined in silico for variabilities in the interaction energies within each group of dsDNA molecules of the same GC content. Since the amount of hydrogen bonding depends on the GC content, holding the GC content fixed when examining the differences in interaction energies allows sequence-dependent interactions to be isolated. The nature of sequence-dependent interactions is then dissected using energy decomposition analysis (EDA). By using EDA, the components of the interactions that depend on the neighboring base pairs help explain some of the variability in the interaction energies of the dsDNA molecules despite having the same GC content. This work provides a new paradigm and tool for the study and analysis of the distributions of interaction components in dsDNA with the same GC content using EDA within large-scale quantum chemistry calculations.

Fragment Binding to Kinase Hinge: If Charge Distribution and Local pKa Shifts Mislead Popular Bioisosterism Concepts

Medicinal-chemistry optimization follows strategies replacing functional groups and attaching larger substituents at a promising lead scaffold. Well-established bioisosterism rules are considered, however, it is difficult to estimate whether the introduced modifications really match the required properties at a binding site. The electron density distribution and pKa values are modulated influencing protonation states and bioavailability. Considering the adjacent H-bond donor/acceptor pattern of the hinge binding motif in a kinase, we studied by crystallography a set of fragments to map the required interaction pattern. Unexpectedly, benzoic acid and benzamidine, decorated with the correct substituents, are totally bioisosteric just as carboxamide and phenolic OH. A mono-dentate pyridine nitrogen out-performs bi-dentate functionalities. The importance of correctly designing pKa values of attached functional groups by additional substituents at the parent scaffold is rendered prominent.

Consistent inclusion of continuum solvation in energy decomposition analysis: theory and application to molecular CO2 reduction catalysts

To facilitate computational investigation of intermolecular interactions in the solution phase, we report the development of ALMO-EDA(solv), a scheme that allows the application of continuum solvent models within the framework of energy decomposition analysis (EDA) based on absolutely localized molecular orbitals (ALMOs). In this scheme, all the quantum mechanical states involved in the variational EDA procedure are computed with the presence of solvent environment so that solvation effects are incorporated in the evaluation of all its energy components. After validation on several model complexes, we employ ALMO-EDA(solv) to investigate substituent effects on two classes of complexes that are related to molecular CO2 reduction catalysis. For [FeTPP(CO2-κC)]2- (TPP = tetraphenylporphyrin), we reveal that two ortho substituents which yield most favorable CO2 binding, -N(CH3)3 + (TMA) and -OH, stabilize the complex via through-structure and through-space mechanisms, respectively. The coulombic interaction between the positively charged TMA group and activated CO2 is found to be largely attenuated by the polar solvent. Furthermore, we also provide computational support for the design strategy of utilizing bulky, flexible ligands to stabilize activated CO2 via long-range Coulomb interactions, which creates biomimetic solvent-inaccessible "pockets" in that electrostatics is unscreened. For the reactant and product complexes associated with the electron transfer from the p-terphenyl radical anion to CO2, we demonstrate that the double terminal substitution of p-terphenyl by electron-withdrawing groups considerably strengthens the binding in the product state while moderately weakens that in the reactant state, which are both dominated by the substituent tuning of the electrostatics component. These applications illustrate that this new extension of ALMO-EDA provides a valuable means to unravel the nature of intermolecular interactions and quantify their impacts on chemical reactivity in solution.

Molecular Dynamics Simulations with NAMD2

X-ray diffraction crystallography is the primary technique to determine the three-dimensional structures of biomolecules. Although a robust method, X-ray crystallography is not able to access the dynamical behavior of macromolecules. To do so, we have to carry out molecular dynamics simulations taking as an initial system the three-dimensional structure obtained from experimental techniques or generated using homology modeling. In this chapter, we describe in detail a tutorial to carry out molecular dynamics simulations using the program NAMD2. We chose as a molecular system to simulate the structure of human cyclin-dependent kinase 2.

The ONETEP linear-scaling density functional theory program

We present an overview of the onetep program for linear-scaling density functional theory (DFT) calculations with large basis set (plane-wave) accuracy on parallel computers. The DFT energy is computed from the density matrix, which is constructed from spatially localized orbitals we call Non-orthogonal Generalized Wannier Functions (NGWFs), expressed in terms of periodic sinc (psinc) functions. During the calculation, both the density matrix and the NGWFs are optimized with localization constraints. By taking advantage of localization, onetep is able to perform calculations including thousands of atoms with computational effort, which scales linearly with the number or atoms. The code has a large and diverse range of capabilities, explored in this paper, including different boundary conditions, various exchange-correlation functionals (with and without exact exchange), finite electronic temperature methods for metallic systems, methods for strongly correlated systems, molecular dynamics, vibrational calculations, time-dependent DFT, electronic transport, core loss spectroscopy, implicit solvation, quantum mechanical (QM)/molecular mechanical and QM-in-QM embedding, density of states calculations, distributed multipole analysis, and methods for partitioning charges and interactions between fragments. Calculations with onetep provide unique insights into large and complex systems that require an accurate atomic-level description, ranging from biomolecular to chemical, to materials, and to physical problems, as we show with a small selection of illustrative examples. onetep has always aimed to be at the cutting edge of method and software developments, and it serves as a platform for developing new methods of electronic structure simulation. We therefore conclude by describing some of the challenges and directions for its future developments and applications.

Charge transfer as a ubiquitous mechanism in determining the negative charge at hydrophobic interfaces

The origin of the apparent negative charge at hydrophobic–water interfaces has fueled debates in the physical chemistry community for decades. The most common interpretation given to explain this observation is that negatively charged hydroxide ions (OH^–) bind strongly to the interfaces. Using first principles calculations of extended air–water and oil–water interfaces, we unravel a mechanism that does not require the presence of OH^–. Small amounts of charge transfer along hydrogen bonds and asymmetries in the hydrogen bond network due to topological defects can lead to the accumulation of negative surface charge at both interfaces. For water near oil, some spillage of electron density into the oil phase is also observed. The computed surface charge densities at both interfaces is approximately \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$-0.015\ {\rm{e}}/{{\rm{nm}}}^{2}$$\end{document}−0.015e∕nm2 in agreement with electrophoretic experiments. We also show, using an energy decomposition analysis, that the electronic origin of this phenomena is rooted in a collective polarization/charge transfer effect.

The accumulation of negative charge at hydrophobic–water interfaces has been a source of debate for a long time. Here the authors use ab initio calculations to show that the charge accumulation at air–water and oil–water interfaces is caused by subtle charge transfer processes.

Discovery and design of soft polymeric bio-inspired materials with multiscale simulations and artificial intelligence

Establishing the “Materials 4.0” paradigm requires intimate knowledge of the virtual space in materials design.

Van der Waals Potential in Protein Complexes

Van der Waals forces are determinants of the formation of protein-ligand complexes. Physical models based on the Lennard-Jones potential can estimate van der Waals interactions with considerable accuracy and with a computational complexity that allows its application to molecular docking simulations and virtual screening of large databases of small organic molecules. Several empirical scoring functions used to evaluate protein-ligand interactions approximate van der Waals interactions with the Lennard-Jones potential. In this chapter, we present the main concepts necessary to understand van der Waals interactions relevant to molecular recognition of a ligand by the binding pocket of a protein target. We describe the Lennard-Jones potential and its application to calculate potential energy for an ensemble of structures to highlight the main features related to the importance of this interaction for binding affinity.